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[Special EffectsEM_GM

Description: 混合高斯分布EM算法,可以算混合高斯分布的三个参数。混合高斯分布更接近系数分布。-mixed Gaussian distribution EM algorithm can calculate mixed Gaussian distribution of the three parameters. Mixed closer to the Gaussian distribution coefficient.
Platform: | Size: 9216 | Author: 连强 | Hits:

[Mathimatics-Numerical algorithmsuniformgauss

Description: 均匀分布的随机数,并依此产生高斯分布随机数,12和法和Box-Muller法产生高斯分布-uniform distribution of random numbers, and so have a Gaussian distribution of random numbers, 12 and the law and Box-Muller method, Gaussian distribution
Platform: | Size: 1024 | Author: 吴俊 | Hits:

[Otherzjf147

Description: 用来产生均匀分布或高斯分布的伪随机数 (近似白噪声),它们可具有不同的均值和方差。用REMEZ算法求交错点组。用Cholesky分解求ARMA模型的参数并作谱估计。求MA模型的参数 并估计功率谱。 用最小方差法估计序列 的功率谱。-used to produce uniform or Gaussian distribution of the pseudo-random number (similar to white noise). They may have a different mean and variance. Application of Remez algorithm used for staggered Point Group. Cholesky decomposition used for ARMA model and the parameters estimated for the spectrum. MA for the model parameters and the estimated power spectrum. With MVM sequence of the estimated power spectrum.
Platform: | Size: 5120 | Author: zhoujianfang | Hits:

[Othergn

Description: 产生符合均匀分布、高斯分布、指数分布、泊松分布,伽玛分布等的随机数-Produced in line with the uniform distribution, Gaussian distribution, exponential distribution, Poisson distribution, gamma distribution of the random number
Platform: | Size: 144384 | Author: wb | Hits:

[matlabem

Description: 高斯分布期望优化(em)算法matlab实现,流量矩阵模型-Optimization of Gaussian distribution expectations (em) algorithm matlab realized, the flow matrix model
Platform: | Size: 3072 | Author: jiangzhi | Hits:

[Data structsGsfbsjs

Description: 高斯分布随机数源代码,一个很简单实用的程序-Gaussian distribution random number source code, a very simple and practical procedures
Platform: | Size: 5120 | Author: zhanggg | Hits:

[Communicationrandomdata

Description: 用C语言编写随机信号的产生:包括均匀分布,高斯分布,二项式分布,锐利分布, 对数高斯分布,泊松分布,拉普拉斯等分布。-Using C language of the generated random signal: including uniform distribution, Gaussian distribution, binomial distribution, a sharp distribution, logarithm Gaussian distribution, Poisson distribution, Laplace distribution.
Platform: | Size: 2235392 | Author: | Hits:

[Speech/Voice recognition/combinemixtureofgauss

Description: 语音识别中用做联合高斯分布的matlab源代码-Does speech recognition with a joint Gaussian distribution of the matlab source code
Platform: | Size: 2048 | Author: 夭淼 | Hits:

[matlabmatlabdesigning1

Description: 产生一均匀分布的白噪声信产生均匀分布的白噪信号,使均值为0,功率为p号u(n),画出其波形,并检验其分布情况,产生零均值功率0.1且服从高斯分布的白噪声,sinc信号,chirp信号,线性卷积-Generate uniformly distributed one letter of the white noise generated uniformly distributed white noise signal, so that the mean is 0, the power for the p number u (n), draw their waveforms, and test its distribution, resulting in zero average power of 0.1 and subject to Gaussian distribution of white noise, sinc signals, chirp signals, the linear convolution
Platform: | Size: 8192 | Author: 白璐 | Hits:

[matlabweibull

Description: 这是雷达幅度符合韦布尔分布的杂波仿真程序,功率谱为高斯谱,时域上分为I、Q两路。-This is consistent with the Weibull distribution range radar clutter simulation program, power spectrum for the Gaussian spectrum, the time domain is divided into I, Q two.
Platform: | Size: 1024 | Author: xuwei | Hits:

[AI-NN-PRParzen_Window

Description: 模式识别中Parzen窗函数的实现,模拟对二维高斯分布的非参估计。窗函数有三种:高斯窗、指数窗、方窗-Pattern Recognition Parzen window function of the realization, simulation of two-dimensional Gaussian distribution is estimated non-participation. There are three window function: Gaussian window, the index window, side windows
Platform: | Size: 4096 | Author: 唐盛 | Hits:

[matlabguass

Description: 基于MATLAB,可以方便地产生随机数,均匀分布和高斯分布等 -Based on MATLAB, can easily generate random numbers, uniform distribution and Gaussian distribution
Platform: | Size: 1024 | Author: shaoyqo | Hits:

[Special Effectscode

Description: 视频运动物体检测,采用混合高斯分布建立背景模型及差分方法对背景模型进行更新-Sports video object detection, adopt a mixed Gaussian distribution model and set up the background difference method to update the background model
Platform: | Size: 1024 | Author: 齐欣 | Hits:

[AI-NN-PRcode

Description: 本贝叶斯分类器可以实现对二维高斯分布样本的分类-The Bayesian classifier can achieve two-dimensional Gaussian distribution of the classification of samples
Platform: | Size: 3072 | Author: maling | Hits:

[Special EffectsOptimumThrsholding

Description: 编写实现最优阈值方法。假设目标和背景的分布为高斯分布。程序的输入参数根据公式要求而定。将得到的值作为程序输入的参数,对图像进行分割。-Preparation methods to achieve the optimal threshold. The assumption that the distribution of the target and background for the Gaussian distribution. Procedures in accordance with the formula of the input parameter requirements. The value will be entered as the process parameters, image segmentation.
Platform: | Size: 60416 | Author: jhm | Hits:

[matlabEM_GM_fast

Description: EM算法的高斯分布的MATLAB程序源码实现-EM Algorithm for Gaussian distribution of the MATLAB program source code to achieve
Platform: | Size: 3072 | Author: 夏常源 | Hits:

[Special EffectsMATLAB_Medical_Image_Process_Experiments

Description: MATLAB医学影像处理实验(内含14个原代码及教学的说明) (1)Plot a sine function using MATLAB, and write the data into a file (2)Read data from a file, plot a SINC function, and append the result back to the same file (3)Plot a Gaussian distribution using MATLAB (4)Fourier transform of a square function is a SINC function (5)1-D low-pass filters and their point-spread functions (6)2-D low-pass filters and their point-spread functions (7)Fourier Transform of circles and an ellipse (8)Image rotation and magnification (9)MR k-space data reconstruction and low-pass filter (10)Display an image in gray level (11)Display an image in color (12)Region of interest selection and display (13)Cross correlation between temperature and humidity (14)Independent component analysis of mixed music files -MATLAB Medical Image Process Experiments (including 14 source code and course documents) (1)Plot a sine function using MATLAB, and write the data into a file (2)Read data from a file, plot a SINC function, and append the result back to the same file (3)Plot a Gaussian distribution using MATLAB (4)Fourier transform of a square function is a SINC function (5)1-D low-pass filters and their point-spread functions (6)2-D low-pass filters and their point-spread functions (7)Fourier Transform of circles and an ellipse (8)Image rotation and magnification (9)MR k-space data reconstruction and low-pass filter (10)Display an image in gray level (11)Display an image in color (12)Region of interest selection and display (13)Cross correlation between temperature and humidity (14)Independent component analysis of mixed music files
Platform: | Size: 2280448 | Author: 江儜昶 | Hits:

[Algorithmrand_gen

Description: 随即分布数据产生的程序,产生均匀分布、瑞利分布、标准高斯分布、莱斯分布的随机变量-Then the distribution of data generation process, resulting in uniform distribution, Rayleigh distribution, the standard Gaussian distribution, Rice distribution of the random variable
Platform: | Size: 124928 | Author: 杨光 | Hits:

[OtherlocalRand

Description: 常用随机数发生器,C实现 /* * 文件包含了6个函数,它们能产生符合相应分布的规律的随机数: * GenUniformRnd : 产生一个随机数,符合均匀分布。(伪随机序列) * GenBernoulliRnd : 产生一个随机数,符合伯努利分布。 * GenBinomialRnd : 产生一个随机数,符合二项分布。 * GenPoissonRnd : 产生一个随机数,符合泊松分布。 * GenExponentRnd : 产生一个随机数,符合指数分布。 * GenGaussRnd : 产生一个随机数,符合高斯分布。 */-Common random number generator, C implementation /** file contains six functions, they can produce in line with the corresponding distribution laws of random numbers:* GenUniformRnd: generate a random number, in line with evenly distributed. (Pseudo-random sequence)* GenBernoulliRnd: generate a random number, in line with the Bernoulli distribution.* GenBinomialRnd: generate a random number, in line with binomial distribution.* GenPoissonRnd: generate a random number, in line with Poisson distribution.* GenExponentRnd: generate a random number, in line with exponential distribution.* GenGaussRnd: generate a random number, in line with Gaussian distribution.* /
Platform: | Size: 1024 | Author: lo | Hits:

[Algorithmgmm

Description: A common method for real-time segmentation of moving regions in image sequences involves “background subtraction,” or thresholding the error between an estimate of the image without moving objects and the current image. The numerous approaches to this problem differ in the type of background model used and the procedure used to update the model. This paper discusses modeling each pixel as a mixture of Gaussians and using an on-line approximation to update the model. The Gaussian distributions of the adaptive mixture model are then evaluated to determine which are most likelyt o result from a background process. Each pixel is classified based on whether the Gaussian distribution which represents it most effectivelyis considered part of the background model.
Platform: | Size: 186368 | Author: ajinkya | Hits:
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